Decision-Making Styles of Russian School Principals
Bibliographic record
Abstract
In this article, we discuss the results of a pilot project implemented in 2013–2014 within the frame of the Asia Leadership Project international comparative study, which continues research of school leadership in Europe and America started in 2006–2008. Apart from Russia, the pilot project also involved Australia, Hong Kong, Indonesia, Malaysia, and Singapore. Having analyzed statistical reports on the Russian Federation as a whole, as well as on Moscow and Krasnoyarsk Krai in particular, we created a picture of an average school principal and identified their specific features across the regions (age, gender, years of experience, competencies, etc). Upon investigation of decision-making styles (A. Rowe’s Decision Style Inventory) used by school principals in Moscow and Krasnoyarsk and by award winners in the School Principal professional competition, we found out that contextual factors, personal and professional attitudes of a school principal have considerable effects on the school leadership style. The paper also gives an insight into the changes in school leadership styles in the recent decades, managerial methods used by Russian school principals, similarities and differences between school leadership practices in Russia and Canada. As it turned out, the directive decision-making style prevails in practices of both Moscow and Krasnoyarsk Krai school principals. The same style, which discourages efficient interaction between school administrators and teachers, is largely adopted by Canadian school principals even after education reforms implemented in the country. Meaningfully different results were demonstrated by the sample consisting of school principals who had won in the professional competition: about 60 % among them use the conceptual school leadership style on a regular basis. Finally, we describe the conception and design of a large-scale study of the issues in question which is scheduled for future.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".